awesome-R
worldfootballR
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awesome-R | worldfootballR | |
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6 | 7 | |
5,781 | 408 | |
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4.0 | 9.0 | |
about 2 months ago | 3 months ago | |
R | R | |
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Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
awesome-R
- Good coding groups for black women?
- Where to learn R?
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Crantastic: What happened to it?
Won't cover newer ones, but Awesome R has a good list as does this site.
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Setup local development environment for R-yaml
First we looked for a project to play with. Checked the r projects, then looked at the awesome-R list and found r-yaml. We thought a library dealing with YAML files will be simple to install and test.
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WEBSITE WITH TEMPLATES
I can't really decipher what exactly do you want/mean but here you go: https://github.com/qinwf/awesome-R
- Python vs Matlab vs R
worldfootballR
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[OC] Attacking Productivity: Who is Over-performing this Season and Who has been Lucky?
I found this the other day though, where there is an R package with what looks like a good amount of data. So, when I'm ready I might explore this as this might be the best approach to pull in a lot more players more easily.
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Daily Discussion
https://jaseziv.github.io/worldfootballR/ works really well with publicly available data and does most of the data scraping for you, but if you wanted to access paid stuff then you’ll need something else.
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[OC] A Data Dive into Spurs (lack of) Sub Usage (2nd Least Sub Minutes in League Play)
Data is from FotMob and grabbed via worldfootballR. Highly recommend to anyone looking to play around with soccer data, it's super well documented (as is everything in SportsDataverse). It doesn't have player location and all the advanced stuff but has a lot of rich shot data + match stats/events. worldfootballR has a bunch of fb-ref, understat, and transfermarket data as well.
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data sets about Scottish football
There’s an R package called worldfootballR that can be used to extract data from FBref, Transfermarkt, Understat and FotMob. Most of those sites don’t carry much data about Scottish football but FotMob have some really useful shot location data with xG and xGOT values. Here’s the link to the package: https://github.com/JaseZiv/worldfootballR
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[Q] Looking for downloadable football (soccer) statistics
The worldfootballr R package can help you download from some of the big ones.
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[OC] Liverpool and Real Madrid's paths through the knock out stages to the Champions League final
Source:WorldfootballR package
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[OC] Liverpool Substitutions Using worldfootballR and GT
Data extracted using worldfootballR
What are some alternatives?
fontawesome - Easily insert FontAwesome icons into R Markdown docs and Shiny apps
dplyr - dplyr: A grammar of data manipulation
easystats - :milky_way: The R easystats-project
blogdown - Create Blogs and Websites with R Markdown
sf - Simple Features for R
ggplot2 - An implementation of the Grammar of Graphics in R
lab02_R_intro - Vežbe 2: Uvod u R
wesanderson - A Wes Anderson color palette for R
viridis - Colorblind-Friendly Color Maps for R
epanet2toolkit - An R package for calling the Epanet software for simulation of piping networks.
fastverse - An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R
soccerdata - ⛏⚽ Scrape soccer data from Club Elo, ESPN, FBref, FiveThirtyEight, Football-Data.co.uk, FotMob, Sofascore, SoFIFA, Understat and WhoScored.